Run “route -n” command to check the current routes on each PC. Then use “ip route flush table main” command to clear the routing tables. Also, we need to enable IP forwarding on the routers.

Since PC 1 is only connected to subnet 1, we first add a route to subnet 1 using following command:

$ route add -net 10.0.0.0 netmask 255.255.255.0 gw 10.0.0.1

To connect PC 1 to other subnets on the network, we either need to add other subnets addresses to the routing table one by one or add a default gateway to send all the packets not intended for Subnet 1 to that gateway.

$ route add default gw 10.0.0.2

Similar to PC 1, we can add the routes to other PCs on the network based on the tables in Figure 1.

In asymmetric routing, data packets take different paths to go from source to destination and to come back [source]. To set up an asymmetric network on Linux machines running Ubuntu 16.04, first, we need to configure the systems to act as routers. Let’s consider a network of 3 hosts and 3 routers as Figure 1 shows. The routers are going to be Linux systems bundled with several NICs.

Figure 1. Network layout.

The routers should be able forward the packets from one network interface card’s (NIC) port to the others. In a terminal window, enter the following command under root privileges (only on routers):

sysctl net.ipv4.ip_forward=1

We also need to ensure that packets coming from a different path that they were sent to, are not dropped as well. Enter the following command (only on routers):

sysctl net.ipv4.conf.all.rp_filter=2

Now, we are ready to assign static routes to the machines. We consider following subnets here:

The subnet for Host 1 connection to Router 1: 10.0.1.0/24

The subnet for Host 2 connection to Router 2: 10.0.2.0/24

The subnet for Host 3 connection to Router 3: 10.0.3.0/24

The subnet for Router 1 connection to Router 2: 10.0.4.0/24

The subnet for Router 1 connection to Router 3: 10.0.5.0/24

The subnet for Router 2 connection to Router 3: 10.0.6.0/24

Figure 2 shows the assigned IP address to each port of Linux machines.

Figure 2. Assigned IP addresses to each port.

The only remaining step is to set up routing tables on each system. To assign routes to each machine we use the “route” command in terminal.

Hosts use their own assigned IP address for the gateway to their subnets and the IP address of next hop on the same subnet for the gateway to other networks. For example, Host 1 uses the gateway 10.0.1.2 for network 10.0.1.0 and the gateway 10.0.1.1 to connect to network 10.0.5.0. We run the following commands for these two networks on Host 1:

We need to run the same command to add all the 6 subnets to every host and router on the network. Figure 3 shows the requires routing tables for each machine.

Figure 3. Routing tables for each system. Now we can also add alternate routes to the same network with a higher metric (lower priority) using the “route” command. For example, we could add the following backup route to Router 2:

route add -net 10.0.3.0 netmask 255.255.255.0 gw 10.0.4.1 metric 100

We can test this route by running ping command on a specific interface of router 2:

First, we need to understand the Bayesian probability. Bayes rule is formulated as follows [1]:

To explain this equation, consider the following:

P(A) = Probability that people like red apples.

P(B) = Probability that people like golden apples.

Now, P(B|A) is the probability that those people who liked red apples also like golden apples.

Finally, from the information given we would like to calculate how many people who like golden apples also like red apples, i.e., P(A|B).

P(A) = 40%

P(B) = 60%

P(B|A) = 50%

P(A|B) =?

Let’s see how we can use Bayes theorem for classification problems. Consider that B is a given data. And A is your conjecture, which you’d like to calculate the possibility for it to be true, i.e., P(A|B). Now, if you calculate P(A|B) for i different conjectures, then the classification problem becomes finding the maximum P(Ai|B). This maximum value is also called Maximum a Posteriori (MAP) [2].

Since, B was a given data, P(B) is constant, and we have:

For a large i, calculating the joint probability becomes impractical. To overcome this problem, we use a naïve assumption, that conjectures are not correlated to each other. With this assumption, we can calculate the as: